name string | body string | score int64 | controversiality int64 | created timestamp[us] | author string | collapsed bool | edited timestamp[us] | gilded int64 | id string | locked bool | permalink string | stickied bool | ups int64 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
t1_ji1k637 | Yeah this was really easy to do with SD using auto1111. I hope this becomes a thing soon with models trained on specialized knowledge datasets. | 2 | 0 | 2023-04-28T11:58:16 | darkjediii | false | null | 0 | ji1k637 | false | /r/LocalLLaMA/comments/131nayh/anyone_got_to_model_merging_yet/ji1k637/ | false | 2 |
t1_ji1jqbl | Yes, serge and a few [other GUIs](https://github.com/underlines/awesome-marketing-datascience/blob/master/awesome-ai.md#other-guis) just work. But I prefer textgen for the available API and easy extensions. While serge is definitely nice to look at. | 20 | 0 | 2023-04-28T11:54:11 | _underlines_ | false | null | 0 | ji1jqbl | false | /r/LocalLLaMA/comments/131nnis/serge_just_works/ji1jqbl/ | false | 20 |
t1_ji1j3tx | Vicuna 13b is even better
Dish-a-ploy - A play on words combining "dish" with "disaster," reflecting the potential for accidents when opening a running dishwasher.
Rinse-risk - Combining "rinse" (as in the cleaning cycle of a dishwasher) and "risk," highlighting the hazard associated with opening the appli... | 8 | 0 | 2023-04-28T11:48:17 | Famberlight | false | null | 0 | ji1j3tx | false | /r/LocalLLaMA/comments/131p1k9/saw_someone_asking_this_to_chatgpt_and_tried_the/ji1j3tx/ | false | 8 |
t1_ji1iypj | Coool... Many thanks for checking and letting me know! | 2 | 0 | 2023-04-28T11:46:57 | involviert | false | null | 0 | ji1iypj | false | /r/LocalLLaMA/comments/12z9znh/new_7b_llama_model_wizardlm_now_available/ji1iypj/ | false | 2 |
t1_ji1iy4f | Plan on doing the int4 65b on P40 and 3090 so I guess I will see how this all works in practice when my parts come and what kind of response times I get. It will be PCIE3x16 full speed.
Loading taking another minute or two doesn't really phase me. Just need sub 30s replies. | 1 | 0 | 2023-04-28T11:46:47 | a_beautiful_rhind | false | 2023-04-28T11:52:50 | 0 | ji1iy4f | false | /r/LocalLLaMA/comments/131i505/how_much_of_a_bottleneck_or_performance_loss_is/ji1iy4f/ | false | 1 |
t1_ji1iy1k | Well sure, it's a pascal chip. Obviously it's not going to keep up with various newer cards. But it's certainly faster than doing it with even a high-end CPU, and it's got 24GB of VRAM. It's far and away the most affordable way to mess around with larger models. If you've only got a couple hundred dollars to waste ... | 2 | 0 | 2023-04-28T11:46:46 | candre23 | false | null | 0 | ji1iy1k | false | /r/LocalLLaMA/comments/130b1ng/good_computer_spec_for_the_next_5_years_to_be/ji1iy1k/ | false | 2 |
t1_ji1gmjd | [deleted] | 1 | 0 | 2023-04-28T11:23:45 | [deleted] | true | null | 0 | ji1gmjd | false | /r/LocalLLaMA/comments/12z9znh/new_7b_llama_model_wizardlm_now_available/ji1gmjd/ | false | 1 |
t1_ji1fbw4 | This is basically a requirement for this model. | 1 | 0 | 2023-04-28T11:10:09 | PauNoCuDoRedditBR | false | null | 0 | ji1fbw4 | false | /r/LocalLLaMA/comments/131lpfm/can_anyone_explain_why_wizard_7b_4bit_128g_seems/ji1fbw4/ | false | 1 |
t1_ji1eael | Set cache = True in the config to get also way faster speed (Tokens / sec) | 7 | 0 | 2023-04-28T10:58:48 | zBlackVision11 | false | null | 0 | ji1eael | false | /r/LocalLLaMA/comments/131lpfm/can_anyone_explain_why_wizard_7b_4bit_128g_seems/ji1eael/ | false | 7 |
t1_ji1e9vw | >I'm wondering why it would be slower than on a 1080 though.
1080 is quite capable card (you are comparing low end of newer generation with high end of older generation). I think 1080 might be just faster in some scenarios. | 1 | 0 | 2023-04-28T10:58:39 | VertexMachine | false | null | 0 | ji1e9vw | false | /r/LocalLLaMA/comments/12z9znh/new_7b_llama_model_wizardlm_now_available/ji1e9vw/ | false | 1 |
t1_ji1e4il | [deleted] | 3 | 0 | 2023-04-28T10:57:00 | [deleted] | true | null | 0 | ji1e4il | false | /r/LocalLLaMA/comments/1313b0q/oobabooga_vicuna_13b_seems_to_get_lost_after/ji1e4il/ | false | 3 |
t1_ji1dst7 | This could be an interesting unitary base from where we can extrapolate eta for the larger models. The Llama paper has information on training setup and duration:
>
> When training a 65B-parameter model, our code
> processes around 380 tokens/sec/GPU on 2048
> A100 GPU with 80GB of RAM. This means that
> training over... | 3 | 0 | 2023-04-28T10:53:22 | Rogerooo | false | 2023-04-28T11:07:26 | 0 | ji1dst7 | false | /r/LocalLLaMA/comments/131ggz4/apparently_someone_has_already_trained_a_1b/ji1dst7/ | false | 3 |
t1_ji1dgnq | If you're moving the model itself, yes. But if you've already split the model, so you've got half of the layers on one GPU and half on another, say, then the only thing that has to be copied across during inference is the hidden state, at the point where the model is split. That's on the order of maybe 20 MB (for the w... | 3 | 0 | 2023-04-28T10:49:33 | ReturningTarzan | false | null | 0 | ji1dgnq | false | /r/LocalLLaMA/comments/131i505/how_much_of_a_bottleneck_or_performance_loss_is/ji1dgnq/ | false | 3 |
t1_ji1db63 | I'd guess so. If it doesn't, it would affect performance anyway, wouldn't it? | 2 | 0 | 2023-04-28T10:47:49 | NickUnrelatedToPost | false | null | 0 | ji1db63 | false | /r/LocalLLaMA/comments/131i505/how_much_of_a_bottleneck_or_performance_loss_is/ji1db63/ | false | 2 |
t1_ji1d9mh | Replaced the config.json with the newest one, now at 2,5-3 tokens/s. Thank you!
I'm wondering why it would be slower than on a 1080 though. | 1 | 0 | 2023-04-28T10:47:19 | monerobull | false | null | 0 | ji1d9mh | false | /r/LocalLLaMA/comments/12z9znh/new_7b_llama_model_wizardlm_now_available/ji1d9mh/ | false | 1 |
t1_ji1cl0m | check new config.json - old one had cache set to false. | 1 | 0 | 2023-04-28T10:39:23 | VertexMachine | false | null | 0 | ji1cl0m | false | /r/LocalLLaMA/comments/12z9znh/new_7b_llama_model_wizardlm_now_available/ji1cl0m/ | false | 1 |
t1_ji1c2bu | Really don't recommend running models on CPU, it's painfully slow compared to GPU.
If you want to run 65b models, just get another 4090.
I think you need 128gb RAM too, to load the model to the VRAM, but not sure.
Alternatively, you could buy 2x used 3090 with 24k VRAM each for less then a single 4090 i think. | 2 | 0 | 2023-04-28T10:33:05 | Overall_Still_7907 | false | null | 0 | ji1c2bu | false | /r/LocalLLaMA/comments/130mscm/what_cpumemory/ji1c2bu/ | false | 2 |
t1_ji1bsz3 | >If one model needs 7GB of VRAM and the other needs 13GB, does this mean I need a total of 20GB of VRAM?
Yes. But you have to be careful with those assumptions. It can be a hard to predict how much VRAM a model needs to run.
>Does the models consume all VRAM they need all the time, or only consume VRAM when they are ... | 6 | 0 | 2023-04-28T10:29:55 | ReturningTarzan | false | null | 0 | ji1bsz3 | false | /r/LocalLLaMA/comments/131fsc1/want_to_run_two_models_at_the_same_time_vram/ji1bsz3/ | false | 6 |
t1_ji1b45y | Awesome! Confirm that it works on my end...
​
(and seriously, just use cache was the fix? :D ) | 2 | 0 | 2023-04-28T10:21:16 | VertexMachine | false | null | 0 | ji1b45y | false | /r/LocalLLaMA/comments/12z9znh/new_7b_llama_model_wizardlm_now_available/ji1b45y/ | false | 2 |
t1_ji18dzx | If you look at the original Standford Alpaca, you'll see they used 4 x A100 but in their GitHub they mention video memory used to be about 120GiB, but this was for 7B.
If you plan on finetuning 7B it should work with a full finetune. | 5 | 0 | 2023-04-28T09:44:53 | 2muchnet42day | false | null | 0 | ji18dzx | false | /r/LocalLLaMA/comments/131g7d8/advice_to_finetune_on_2xa100_80gb_for_7b_13b/ji18dzx/ | false | 5 |
t1_ji18ai7 | [removed] | 1 | 0 | 2023-04-28T09:43:32 | [deleted] | true | 2023-06-15T00:34:50 | 0 | ji18ai7 | false | /r/LocalLLaMA/comments/12z9znh/new_7b_llama_model_wizardlm_now_available/ji18ai7/ | false | 1 |
t1_ji183mh | 3B StableLM with 800B tokens is probably a better option | 1 | 0 | 2023-04-28T09:40:55 | 2muchnet42day | false | null | 0 | ji183mh | false | /r/LocalLLaMA/comments/131ggz4/apparently_someone_has_already_trained_a_1b/ji183mh/ | false | 1 |
t1_ji17rvc | I have an old workstation with an PCI-E 3.0 x8 too. I'd be interested in the answer, too. How do you even make sure the graphics card works at all? I refrained from buying one, because I thought they wouldn't work in the first place?! | 1 | 0 | 2023-04-28T09:36:14 | Magnus_Fossa | false | null | 0 | ji17rvc | false | /r/LocalLLaMA/comments/131i505/how_much_of_a_bottleneck_or_performance_loss_is/ji17rvc/ | false | 1 |
t1_ji17f7b | Thank you for detailed answer! | 1 | 0 | 2023-04-28T09:31:09 | ljubarskij | false | null | 0 | ji17f7b | false | /r/LocalLLaMA/comments/12zg9vf/avx512_on_zen_4/ji17f7b/ | false | 1 |
t1_ji17a3k | Slightly off topic, but I'll say that anyway.
I only have 5900X, and only 32GB of RAM, and a mere 3080 10G. But I managed to run a GPT4-X-Alpaca 30B q4_0 model at an acceptable speed with KoboldCPP.
The prompt ingestion might be sluggish, but there is an --smartcontext optimisation to address that once your prompt is... | 1 | 0 | 2023-04-28T09:29:06 | _Erilaz | false | 2023-04-28T09:35:14 | 0 | ji17a3k | false | /r/LocalLLaMA/comments/12zg9vf/avx512_on_zen_4/ji17a3k/ | false | 1 |
t1_ji1774m | I guess it's something different with my system then. I'm not using booga and I get the opposite, Wizards is insanely fast in loading and generating, Vicuna takes 170 seconds to load and gens a bit slower. I'm also using a RTX 3060 12gb. It's just Wizard for some reason is very fast on my system. | 3 | 0 | 2023-04-28T09:27:51 | jetro30087 | false | null | 0 | ji1774m | false | /r/LocalLLaMA/comments/131lpfm/can_anyone_explain_why_wizard_7b_4bit_128g_seems/ji1774m/ | false | 3 |
t1_ji1724b | it's smol, try it and report back | 3 | 0 | 2023-04-28T09:25:50 | a_beautiful_rhind | false | null | 0 | ji1724b | false | /r/LocalLLaMA/comments/131ggz4/apparently_someone_has_already_trained_a_1b/ji1724b/ | false | 3 |
t1_ji16t0i | But does moving parts of the model, through offloading, multigpu, etc, actually saturate the link in the first place. | 1 | 0 | 2023-04-28T09:22:08 | a_beautiful_rhind | false | null | 0 | ji16t0i | false | /r/LocalLLaMA/comments/131i505/how_much_of_a_bottleneck_or_performance_loss_is/ji16t0i/ | false | 1 |
t1_ji15ff3 | Looks like it: https://huggingface.co/KoboldAI/OPT-13B-Erebus/blob/main/config.json | 2 | 0 | 2023-04-28T09:01:38 | a_beautiful_rhind | false | null | 0 | ji15ff3 | false | /r/LocalLLaMA/comments/12z9znh/new_7b_llama_model_wizardlm_now_available/ji15ff3/ | false | 2 |
t1_ji14x9n | [deleted] | 2 | 0 | 2023-04-28T08:54:04 | [deleted] | true | null | 0 | ji14x9n | false | /r/LocalLLaMA/comments/12z9znh/new_7b_llama_model_wizardlm_now_available/ji14x9n/ | false | 2 |
t1_ji14l2r | Just opened it in my copy of Oobabooga. Loaded Wizard in 12.59 seconds. Which is about how long it takes to generate each token, apparently. I don't mind sacrificing a little load time for better speeds in other models.
Loaded the model in 12.59 seconds.
Output generated in 163.41 seconds (0.07 tokens/s, 12 tokens, c... | 6 | 0 | 2023-04-28T08:48:59 | DeylanQuel | false | 2023-04-28T08:54:29 | 0 | ji14l2r | false | /r/LocalLLaMA/comments/131lpfm/can_anyone_explain_why_wizard_7b_4bit_128g_seems/ji14l2r/ | false | 6 |
t1_ji13vw3 | Thanks for the analysis! It's been solved now.
You were very close to spotting it by checking config.json. The answer was that Wizard had `use_cache: false` and all other models had `use_cache: true`
Changing that results in the performance returning to expected levels!
I will definitely be double-checking this for... | 3 | 0 | 2023-04-28T08:38:43 | The-Bloke | false | null | 0 | ji13vw3 | false | /r/LocalLLaMA/comments/12z9znh/new_7b_llama_model_wizardlm_now_available/ji13vw3/ | false | 3 |
t1_ji136tk | If your memory bandwidth is high enough, then your are compute-limited and more cores is better. Otherwise, your are memory bandwidth-limited and a higher clock is better. | 3 | 0 | 2023-04-28T08:28:28 | gammalsvenska | false | null | 0 | ji136tk | false | /r/LocalLLaMA/comments/130mscm/what_cpumemory/ji136tk/ | false | 3 |
t1_ji11yg2 | Ah I didn’t understand that difference caused by RHLF, makes sense. Thanks! I haven’t played around with any of this yet but still interested in understanding the situation. It’s been wild watching this play out! | 1 | 0 | 2023-04-28T08:10:23 | PM_ME_ENFP_MEMES | false | null | 0 | ji11yg2 | false | /r/LocalLLaMA/comments/12zzd7o/llama546b/ji11yg2/ | false | 1 |
t1_ji11ygh | I am not a techie so take with massive grain of salt, but the progress is very fast in this field. I'm unsure if the core LLM will become much easier or cheaper, but it's clear that integrating LLMs with other software just requires a bit more time to make some very capable systems, and I expect a ton of software to in... | 2 | 0 | 2023-04-28T08:10:23 | WyldCard4 | false | null | 0 | ji11ygh | false | /r/LocalLLaMA/comments/13174cv/what_do_you_think_about_the_llm_market_in_the/ji11ygh/ | false | 2 |
t1_ji101sh | Llama 65b hallucinations are pretty similar to what Bing Chat does, maybe llama is a touch worse here but not significantly. I haven't used ChatGPT in a few months so I don't remember how that worked.
I haven't played with system prompts, that's something that only openAI's models have been finetuned for, right? Llama... | 1 | 0 | 2023-04-28T07:42:12 | FullOf_Bad_Ideas | false | null | 0 | ji101sh | false | /r/LocalLLaMA/comments/12zzd7o/llama546b/ji101sh/ | false | 1 |
t1_ji0yxbf | **UPDATE on the GPTQs:**
Until today there were noticeable performance problems on the GPTQs. This has now been resolved.
If you already grabbed the models, re-download the file `config.json` and you will see a speed increase, especially if you're using CUDA GPTQ-for-LLaMa! | 3 | 0 | 2023-04-28T07:26:00 | The-Bloke | false | null | 0 | ji0yxbf | false | /r/LocalLLaMA/comments/12z9znh/new_7b_llama_model_wizardlm_now_available/ji0yxbf/ | false | 3 |
t1_ji0yfst | The performance issues are fixed! It was a one-word problem!
In `config.json`:
`use_cache: false` should have been `use_cache: true`.
Simple as that! Now performance matches other 7B models.
I've updated `config.json` in the repo and made a note in the README. Either re-download this file, or edit it locally.
And ... | 3 | 0 | 2023-04-28T07:19:10 | The-Bloke | false | null | 0 | ji0yfst | false | /r/LocalLLaMA/comments/12z9znh/new_7b_llama_model_wizardlm_now_available/ji0yfst/ | false | 3 |
t1_ji0xt9w | Try out: https://github.com/go-skynet/LocalAI
Added an example to run local models + chatbot-ui | 2 | 0 | 2023-04-28T07:10:22 | mkellerman_1 | false | null | 0 | ji0xt9w | false | /r/LocalLLaMA/comments/130turq/best_model_to_summarize_text_on_mac/ji0xt9w/ | false | 2 |
t1_ji0wiol | Thanks for responding.
I found StableLM, GPT4All-J and RedPajama. With Dolly 2.0 there are 4 options now available, that are completely free, open source and can be used commercially | 1 | 0 | 2023-04-28T06:52:48 | Koliham | false | null | 0 | ji0wiol | false | /r/LocalLLaMA/comments/1301nmj/licence_of_the_llm_models/ji0wiol/ | false | 1 |
t1_ji0w1ab | Stability failed incredibly hard on the data setting front from the looks of it. They've got a bunch of Reddit in there with names changed to User:, they're padding the context with end tokens, too much focus on short response so the model goes squirrel monkey. That's where I think it stands. They're retraining though.... | 2 | 0 | 2023-04-28T06:46:22 | teachersecret | false | null | 0 | ji0w1ab | false | /r/LocalLLaMA/comments/13174cv/what_do_you_think_about_the_llm_market_in_the/ji0w1ab/ | false | 2 |
t1_ji0vpvr | HuggingFace is using **oasst-sft-6-llama-30b** so it should be good :)
You can test it on their chat. | 3 | 0 | 2023-04-28T06:42:12 | DingWrong | false | null | 0 | ji0vpvr | false | /r/LocalLLaMA/comments/12zsjhf/what_is_the_best_current_local_llm_to_run/ji0vpvr/ | false | 3 |
t1_ji0vo30 | Yeah yeah, but he says he's a software guy and just wants to build stuff around them, so... Basically want people to know where the breakeven is and why you might choose local regardless of cost. | 3 | 0 | 2023-04-28T06:41:31 | randomqhacker | false | null | 0 | ji0vo30 | false | /r/LocalLLaMA/comments/130b1ng/good_computer_spec_for_the_next_5_years_to_be/ji0vo30/ | false | 3 |
t1_ji0vijp | I shouldn't have bothered responding.
Use Dolly 2.0. | 1 | 0 | 2023-04-28T06:39:29 | gammalsvenska | false | null | 0 | ji0vijp | false | /r/LocalLLaMA/comments/1301nmj/licence_of_the_llm_models/ji0vijp/ | false | 1 |
t1_ji0vglr | I responded to "try accessing the cloud without desktop". Sure, use a mobile device for accessing the cloud, then. | 1 | 0 | 2023-04-28T06:38:46 | gammalsvenska | false | null | 0 | ji0vglr | false | /r/LocalLLaMA/comments/12zif1v/are_we_replicating_the_failures_leading_to_lack/ji0vglr/ | false | 1 |
t1_ji0v1g5 | I haven't tried this myself but it looks really interesting. Maybe you can get longer conversations?
[Virtual context for ooga](https://github.com/oobabooga/text-generation-webui/pull/1548) | 2 | 0 | 2023-04-28T06:33:13 | delgrey | false | null | 0 | ji0v1g5 | false | /r/LocalLLaMA/comments/1313b0q/oobabooga_vicuna_13b_seems_to_get_lost_after/ji0v1g5/ | false | 2 |
t1_ji0ur9r | The base/pretrained model is far more important, not the instruction training data that's later finetuned. And LLaMA itself just isn't there yet at smaller sizes (benchmarks are useless for LLMs).
Scale still matters as the model becomes cleverer past 7B. It only significantly feels cleverer past 20B, with 30B probabl... | 3 | 0 | 2023-04-28T06:29:31 | CKtalon | false | 2023-04-28T06:37:00 | 0 | ji0ur9r | false | /r/LocalLLaMA/comments/13174cv/what_do_you_think_about_the_llm_market_in_the/ji0ur9r/ | false | 3 |
t1_ji0ucfc | I've used other models on my 1070 8gb and they worked fine as long as I didn't run out of vram. I'm assuming this one will work too as long as 8gb vram is enough. Gonna give it a try soon | 2 | 0 | 2023-04-28T06:24:05 | KeyOrganization6211 | false | null | 0 | ji0ucfc | false | /r/LocalLLaMA/comments/12z9znh/new_7b_llama_model_wizardlm_now_available/ji0ucfc/ | false | 2 |
t1_ji0u4hq | You run the command in Command Prompt. You need to use the actual path to your main.exe file. | 1 | 0 | 2023-04-28T06:21:18 | Civil_Collection7267 | false | null | 0 | ji0u4hq | false | /r/LocalLLaMA/comments/131i62l/issue_with_running/ji0u4hq/ | true | 1 |
t1_ji0txth | This question should be posted in r/StableDiffusion. | 1 | 0 | 2023-04-28T06:18:53 | Civil_Collection7267 | false | null | 0 | ji0txth | false | /r/LocalLLaMA/comments/131eu5b/is_there_a_cpp_wrapper_for_stable_diffusion/ji0txth/ | true | 1 |
t1_ji0th1p | If your model fits into your VRAM, I shouldn't be bad. You just have to send the model to the GPU once. Doesn't matter if that takes double the time.
If you offload parts of the model to system RAM your performance will be hurt quite a bit, because the offloaded part has to be send of PCI once per iteration. | 4 | 0 | 2023-04-28T06:12:50 | NickUnrelatedToPost | false | null | 0 | ji0th1p | false | /r/LocalLLaMA/comments/131i505/how_much_of_a_bottleneck_or_performance_loss_is/ji0th1p/ | false | 4 |
t1_ji0ted7 | Oh, well guess my 1650 is just gonna be sitting there | 2 | 0 | 2023-04-28T06:11:52 | kedarkhand | false | null | 0 | ji0ted7 | false | /r/LocalLLaMA/comments/13174cv/what_do_you_think_about_the_llm_market_in_the/ji0ted7/ | false | 2 |
t1_ji0tdll | Not particularly. Even if 30b is the wall, we can run 30b right now at a perfectly acceptable speed on a modern CPU, and fast on a higher end 24gb gpu. You can even run 65b if you want. Sure, it's slower, but it's just as smart and an answer in a minute instead of ten seconds is still plenty useful, especially if it's ... | 3 | 0 | 2023-04-28T06:11:37 | teachersecret | false | null | 0 | ji0tdll | false | /r/LocalLLaMA/comments/13174cv/what_do_you_think_about_the_llm_market_in_the/ji0tdll/ | false | 3 |
t1_ji0tch9 | Idk, the SD is very small and the core model part is never in python anyways. Feels like people that cared about speed would have had a gpu anyways | 1 | 0 | 2023-04-28T06:11:14 | Faintly_glowing_fish | false | null | 0 | ji0tch9 | false | /r/LocalLLaMA/comments/131eu5b/is_there_a_cpp_wrapper_for_stable_diffusion/ji0tch9/ | false | 1 |
t1_ji0t79e | the question isn't about CPU, the question is about C++ | 1 | 0 | 2023-04-28T06:09:22 | Tystros | false | null | 0 | ji0t79e | false | /r/LocalLLaMA/comments/131eu5b/is_there_a_cpp_wrapper_for_stable_diffusion/ji0t79e/ | false | 1 |
t1_ji0s7sg | I'm not. I'm using the oobabooga api. Gpu run. | 2 | 0 | 2023-04-28T05:56:50 | teachersecret | false | null | 0 | ji0s7sg | false | /r/LocalLLaMA/comments/13174cv/what_do_you_think_about_the_llm_market_in_the/ji0s7sg/ | false | 2 |
t1_ji0s4n6 | how are you running autogpt with llamacpp? I have been trying but unsuccessful so far | 1 | 0 | 2023-04-28T05:55:45 | kedarkhand | false | null | 0 | ji0s4n6 | false | /r/LocalLLaMA/comments/13174cv/what_do_you_think_about_the_llm_market_in_the/ji0s4n6/ | false | 1 |
t1_ji0r6iu | [deleted] | 1 | 0 | 2023-04-28T05:44:23 | [deleted] | true | null | 0 | ji0r6iu | false | /r/LocalLLaMA/comments/130b1ng/good_computer_spec_for_the_next_5_years_to_be/ji0r6iu/ | false | 1 |
t1_ji0qqzl | We are pretty much at a bottleneck at 4 bit. Research shows that 3 bit just doesn’t cut it. LLMs need to be at least 30B to really even have a chance of comparing with GPT4. You are just being overly optimistic. | 2 | 0 | 2023-04-28T05:39:15 | CKtalon | false | null | 0 | ji0qqzl | false | /r/LocalLLaMA/comments/13174cv/what_do_you_think_about_the_llm_market_in_the/ji0qqzl/ | false | 2 |
t1_ji0qd4m | >AMD MI25
Ive got a P40, and while it might be ok for inference, its an absolute dog at fine-tuning, especially 8-bit. Unbearably slow. | 3 | 0 | 2023-04-28T05:34:49 | yahma | false | null | 0 | ji0qd4m | false | /r/LocalLLaMA/comments/130b1ng/good_computer_spec_for_the_next_5_years_to_be/ji0qd4m/ | false | 3 |
t1_ji0q4qi | This is already happening. It turns out that training smaller 1b models on much more data is producing results comparable or even surpassing Alpaca-7b. Check this out:
[https://github.com/mbzuai-nlp/lamini-lm/](https://github.com/mbzuai-nlp/lamini-lm/) | 2 | 0 | 2023-04-28T05:32:03 | yahma | false | null | 0 | ji0q4qi | false | /r/LocalLLaMA/comments/130b1ng/good_computer_spec_for_the_next_5_years_to_be/ji0q4qi/ | false | 2 |
t1_ji0q1sz | I think this is a very cost efficient and SoTA method for fine-tuning 7B parameter model - https://lightning.ai/pages/community/tutorial/lora-llm/ | 3 | 0 | 2023-04-28T05:31:06 | ahm_rimer | false | null | 0 | ji0q1sz | false | /r/LocalLLaMA/comments/131g7d8/advice_to_finetune_on_2xa100_80gb_for_7b_13b/ji0q1sz/ | false | 3 |
t1_ji0pj2w | Should be able to by applying the correct flags. | 2 | 0 | 2023-04-28T05:24:54 | Tom_Neverwinter | false | null | 0 | ji0pj2w | false | /r/LocalLLaMA/comments/131fsc1/want_to_run_two_models_at_the_same_time_vram/ji0pj2w/ | false | 2 |
t1_ji0nm8t | It depends on how long the context is. But a few hundred tokens will be a few GB | 1 | 0 | 2023-04-28T05:03:10 | CKtalon | false | null | 0 | ji0nm8t | false | /r/LocalLLaMA/comments/131fsc1/want_to_run_two_models_at_the_same_time_vram/ji0nm8t/ | false | 1 |
t1_ji0mm2l | Do you mean I can allocate a fixed amount of VRAM for one model? | 2 | 0 | 2023-04-28T04:52:07 | regunakyle | false | null | 0 | ji0mm2l | false | /r/LocalLLaMA/comments/131fsc1/want_to_run_two_models_at_the_same_time_vram/ji0mm2l/ | false | 2 |
t1_ji0m7j6 | Thanks for your reply! Is it possible to estimate how much extra VRAM is needed when running inference? | 1 | 0 | 2023-04-28T04:47:48 | regunakyle | false | null | 0 | ji0m7j6 | false | /r/LocalLLaMA/comments/131fsc1/want_to_run_two_models_at_the_same_time_vram/ji0m7j6/ | false | 1 |
t1_ji0m7f6 | Anyone know how to run that model with text generation web ui in paperspace gradient notebook? | 1 | 0 | 2023-04-28T04:47:46 | Conscious_Steak4417 | false | null | 0 | ji0m7f6 | false | /r/LocalLLaMA/comments/12yax3h/wizardlm_finetuned_llama_7b_with_evolving/ji0m7f6/ | false | 1 |
t1_ji0m624 | I also have M1 16GB, any LLaMa 7B or 13B based model will work well. I have tried many models (vanilla llama, alpaca, vicuna, gpt4all, gpt4-x-alpaca, gpt4all and there are many more I have not tried yet) and all are quite similar in term of capabilities. | 2 | 0 | 2023-04-28T04:47:21 | wojtek15 | false | null | 0 | ji0m624 | false | /r/LocalLLaMA/comments/130turq/best_model_to_summarize_text_on_mac/ji0m624/ | false | 2 |
t1_ji0lwpj | [deleted] | 1 | 0 | 2023-04-28T04:44:35 | [deleted] | true | null | 0 | ji0lwpj | false | /r/LocalLLaMA/comments/12zsjhf/what_is_the_best_current_local_llm_to_run/ji0lwpj/ | false | 1 |
t1_ji0l5o8 | In principle I agree - for example, I have perfectly acceptable local models running that are nearly chatgpt in style and quality of responses... but I still send lots of requests to the gpt4 api because it's just... smarter. For many of my uses, I will keep using the big paid model.
But...
I'm also paying for those ... | 6 | 0 | 2023-04-28T04:36:44 | teachersecret | false | 2023-04-28T04:39:49 | 0 | ji0l5o8 | false | /r/LocalLLaMA/comments/13174cv/what_do_you_think_about_the_llm_market_in_the/ji0l5o8/ | false | 6 |
t1_ji0jlg5 | AI capable of running orders on a PC in a year?
I have that on my desk right now... vicuña/auto LLM, and it's rapidly getting better. I've had it do some wild things locally. Only reason I don't use it more is simple: gpt4 is so good it's hard not to use that api instead :).
4 bit quantization is dragging damn-near-c... | 5 | 0 | 2023-04-28T04:20:44 | teachersecret | false | 2023-04-28T04:25:26 | 0 | ji0jlg5 | false | /r/LocalLLaMA/comments/13174cv/what_do_you_think_about_the_llm_market_in_the/ji0jlg5/ | false | 5 |
t1_ji0j9st | [deleted] | 24 | 0 | 2023-04-28T04:17:30 | [deleted] | true | null | 0 | ji0j9st | false | /r/LocalLLaMA/comments/131ggz4/apparently_someone_has_already_trained_a_1b/ji0j9st/ | false | 24 |
t1_ji0j83n | In multi-gpu the MEG Ace x670e runs at
x16/x0/x4 or x8/x8/x4 | 1 | 0 | 2023-04-28T04:17:00 | Zyj | false | null | 0 | ji0j83n | false | /r/LocalLLaMA/comments/130b1ng/good_computer_spec_for_the_next_5_years_to_be/ji0j83n/ | false | 1 |
t1_ji0iu0m | Dude, you're on the wrong subreddit | 2 | 0 | 2023-04-28T04:13:05 | Zyj | false | null | 0 | ji0iu0m | false | /r/LocalLLaMA/comments/130b1ng/good_computer_spec_for_the_next_5_years_to_be/ji0iu0m/ | false | 2 |
t1_ji0is28 | There is an instruction tuned cerebras-gpt model at the same size that speaks very coherently, and this model is way more trained. | 18 | 0 | 2023-04-28T04:12:33 | pokeuser61 | false | null | 0 | ji0is28 | false | /r/LocalLLaMA/comments/131ggz4/apparently_someone_has_already_trained_a_1b/ji0is28/ | false | 18 |
t1_ji0ink7 | Interesting. I'm having no issues running 4x 32GB DDR4 at 3200 | 2 | 0 | 2023-04-28T04:11:18 | Zyj | false | null | 0 | ji0ink7 | false | /r/LocalLLaMA/comments/130b1ng/good_computer_spec_for_the_next_5_years_to_be/ji0ink7/ | false | 2 |
t1_ji0ihxo | That card is priced way higher than the already expensive consumer cards. | 1 | 0 | 2023-04-28T04:09:45 | Zyj | false | null | 0 | ji0ihxo | false | /r/LocalLLaMA/comments/130b1ng/good_computer_spec_for_the_next_5_years_to_be/ji0ihxo/ | false | 1 |
t1_ji0ihmq | Yes. There are some CPU fork for SD | 2 | 0 | 2023-04-28T04:09:41 | Faintly_glowing_fish | false | null | 0 | ji0ihmq | false | /r/LocalLLaMA/comments/131eu5b/is_there_a_cpp_wrapper_for_stable_diffusion/ji0ihmq/ | false | 2 |
t1_ji0i6gj | I did the same but also bought a used AM4 X570 SLI capable board (x8/x8). Even found a cheap 3-slot nvlink bridge for it. | 1 | 0 | 2023-04-28T04:06:37 | Zyj | false | null | 0 | ji0i6gj | false | /r/LocalLLaMA/comments/130b1ng/good_computer_spec_for_the_next_5_years_to_be/ji0i6gj/ | false | 1 |
t1_ji0hqzz | Yes, I have seen LaMini-LM, but haven't played with it yet, I guess I should.
​
I'll take a look at your dataset, I'm really focusing on filtering/selececting, dedupping, and ensuring quality of the instructs and responses.
Kind of digging into what’s actually in the instruct datasets. I don’t think that’s be... | 1 | 0 | 2023-04-28T04:02:28 | wind_dude | false | 2023-04-28T04:16:18 | 0 | ji0hqzz | false | /r/LocalLLaMA/comments/1300fxe/new_llama_lora_trained_on_wizardlm_dataset/ji0hqzz/ | false | 1 |
t1_ji0ge5z | I'm not sure...there's really a point? A 1b model trained on 200b tokens would be lucky to complete a sentence, let alone be useful. | 15 | 0 | 2023-04-28T03:49:53 | TeamPupNSudz | false | null | 0 | ji0ge5z | false | /r/LocalLLaMA/comments/131ggz4/apparently_someone_has_already_trained_a_1b/ji0ge5z/ | false | 15 |
t1_ji0fwoy | [deleted] | 1 | 0 | 2023-04-28T03:45:38 | [deleted] | true | null | 0 | ji0fwoy | false | /r/LocalLLaMA/comments/131bxby/best_model_for_instructional_design_condense_raw/ji0fwoy/ | false | 1 |
t1_ji0f16d | Thanks! I take a closer look at it. And I assumed at this point I’ll have to be creative about fixing up content first to stay within character limit (easier said than done without botching continuity). | 1 | 0 | 2023-04-28T03:37:57 | MyVoiceIsElevating | false | null | 0 | ji0f16d | false | /r/LocalLLaMA/comments/131bxby/best_model_for_instructional_design_condense_raw/ji0f16d/ | false | 1 |
t1_ji0ey3k | Have you seen [LaMini-LM](https://github.com/mbzuai-nlp/lamini-lm/)? They achieve Alpaca-7b performance in a 1.5b model through the use of a very large dataset (2.5M+ instructions).
I created a dataset [merge](https://github.com/gururise/AlpacaDataCleaned/tree/main/dataset_extensions) based on the following very high ... | 1 | 0 | 2023-04-28T03:37:13 | yahma | false | 2023-04-28T03:45:52 | 0 | ji0ey3k | false | /r/LocalLLaMA/comments/1300fxe/new_llama_lora_trained_on_wizardlm_dataset/ji0ey3k/ | false | 1 |
t1_ji0dvsm | Sadly no, but it’s just a matter of time until someone ports it to ggml. | 1 | 0 | 2023-04-28T03:28:08 | pokeuser61 | false | null | 0 | ji0dvsm | false | /r/LocalLLaMA/comments/131eu5b/is_there_a_cpp_wrapper_for_stable_diffusion/ji0dvsm/ | false | 1 |
t1_ji0dekn | Possible to get a link to the Chatbot UI?
Is it this one -[https://github.com/Yidadaa/ChatGPT-Next-Web](https://github.com/Yidadaa/ChatGPT-Next-Web) | 1 | 0 | 2023-04-28T03:24:02 | regstuff | false | null | 0 | ji0dekn | false | /r/LocalLLaMA/comments/130turq/best_model_to_summarize_text_on_mac/ji0dekn/ | false | 1 |
t1_ji0cxzg | If I understand you right, you want to summarize a transcript of an audio?
Similar use case for me.
WizardLM 7B (I use the [GGML version](https://huggingface.co/TheBloke/wizardLM-7B-GGML), but there's proper HF & GPU 4-bit versions on HF as well) does it pretty decent job. I find it is as good or better than ChatGPT ... | 4 | 0 | 2023-04-28T03:20:12 | regstuff | false | null | 0 | ji0cxzg | false | /r/LocalLLaMA/comments/131bxby/best_model_for_instructional_design_condense_raw/ji0cxzg/ | false | 4 |
t1_ji0cix7 | You should have the models loaded in VRAM constantly, otherwise every call you make will require waiting up to a minute to transfer the model from disk to VRAM.
You will also likely need more than 7+13GB if at anytime you are running both models at the same time since the context length and inference part will take up... | 2 | 0 | 2023-04-28T03:16:42 | CKtalon | false | null | 0 | ji0cix7 | false | /r/LocalLLaMA/comments/131fsc1/want_to_run_two_models_at_the_same_time_vram/ji0cix7/ | false | 2 |
t1_ji0c13p | https://github.com/underlines/awesome-marketing-datascience/blob/master/awesome-ai.md#open-models | 1 | 0 | 2023-04-28T03:12:34 | SufficientPie | false | null | 0 | ji0c13p | false | /r/LocalLLaMA/comments/12zgohs/stablelm_7b_multiple_tunes_converted_and_quantized/ji0c13p/ | false | 1 |
t1_ji0bz75 | Depends on the setup.
Some make it so it can only allocate pieces to a singular program. This is how many vm hosts run
Some can spread it across all available v ram | 1 | 0 | 2023-04-28T03:12:07 | Tom_Neverwinter | false | null | 0 | ji0bz75 | false | /r/LocalLLaMA/comments/131fsc1/want_to_run_two_models_at_the_same_time_vram/ji0bz75/ | false | 1 |
t1_ji0bdsn | Where can I apply this parameter? | 1 | 0 | 2023-04-28T03:07:15 | Poopasite1 | false | null | 0 | ji0bdsn | false | /r/LocalLLaMA/comments/1303ay8/models_freeze_after_awhile_running_llamacpp/ji0bdsn/ | false | 1 |
t1_ji09jbp | > Judging by previous revolutionary tech, it always gets cheaper and more available overtime.
It does, but who is running a clothing loom in their garage? I'm sure the at home stuff will get better, but I'm fairly confident the not-at-home-stuff will get so much better so much faster that it simply will not matter. | 1 | 0 | 2023-04-28T02:52:43 | bioemerl | false | null | 0 | ji09jbp | false | /r/LocalLLaMA/comments/13174cv/what_do_you_think_about_the_llm_market_in_the/ji09jbp/ | false | 1 |
t1_ji08i47 | So far.. This is the only solution. I can't stop laughing cause it works. | 3 | 0 | 2023-04-28T02:44:44 | Poopasite1 | false | null | 0 | ji08i47 | false | /r/LocalLLaMA/comments/1303ay8/models_freeze_after_awhile_running_llamacpp/ji08i47/ | false | 3 |
t1_ji08c3y | Do you have a link for the first one? | 1 | 0 | 2023-04-28T02:43:28 | SHADER_MIX | false | null | 0 | ji08c3y | false | /r/LocalLLaMA/comments/130turq/best_model_to_summarize_text_on_mac/ji08c3y/ | false | 1 |
t1_ji07wy0 | I agree. LLMs will be like oil and the real money will be made on products built with it. | 1 | 0 | 2023-04-28T02:40:16 | Pretend_Jellyfish363 | false | null | 0 | ji07wy0 | false | /r/LocalLLaMA/comments/13174cv/what_do_you_think_about_the_llm_market_in_the/ji07wy0/ | false | 1 |
t1_ji07bf4 | This one? https://github.com/EdVince/Stable-Diffusion-NCNN | 1 | 0 | 2023-04-28T02:35:45 | andw1235 | false | null | 0 | ji07bf4 | false | /r/LocalLLaMA/comments/131eu5b/is_there_a_cpp_wrapper_for_stable_diffusion/ji07bf4/ | false | 1 |
t1_ji070f4 | Very unlikely scenario. Judging by previous revolutionary tech, it always gets cheaper and more available overtime.
We know how to build LLMs. It’s not rocket science. I believe we will discover (in the near future) more efficient way of building them with less parameters, data and cheaper hardware.
There are other... | 5 | 0 | 2023-04-28T02:33:24 | Pretend_Jellyfish363 | false | null | 0 | ji070f4 | false | /r/LocalLLaMA/comments/13174cv/what_do_you_think_about_the_llm_market_in_the/ji070f4/ | false | 5 |
t1_ji0572w | Will it ever? Is it something nvidia is considering? | 1 | 0 | 2023-04-28T02:19:56 | EewSquishy | false | null | 0 | ji0572w | false | /r/LocalLLaMA/comments/130b1ng/good_computer_spec_for_the_next_5_years_to_be/ji0572w/ | false | 1 |
t1_ji03g8w | Bank on VRAM.
IMO, I would open PC Part Picker and start going across the parts list like this: GPU (high VRAM, 20GB or so) -> CPU -> PSU -> RAM -> rest.
I am only really confident with the AMD naming scheme and classes; so there I can only really recommend either Ryzen 8 or 9. Even GPU inferences start at the CPU wh... | 6 | 0 | 2023-04-28T02:07:23 | IngwiePhoenix | false | null | 0 | ji03g8w | false | /r/LocalLLaMA/comments/130b1ng/good_computer_spec_for_the_next_5_years_to_be/ji03g8w/ | false | 6 |
t1_ji0277h | Thank you! This is great! | 1 | 0 | 2023-04-28T01:58:13 | SatoshiReport | false | null | 0 | ji0277h | false | /r/LocalLLaMA/comments/131cjki/documentation_on_the_configuration_options/ji0277h/ | false | 1 |
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